In order to improve the reliable operation capability of a combined heat and power microgrid (CHP-MG) in a harsh environment, a fuzzy economic dispatching strategy of CHP-MG considering the double uncertainty of source and load is proposed based on the typical scenarios of wind, light, electricity and heat. Firstly, a combination method of Latin Hypercube Sampling (LHS) and K-means clustering is used to generate typical scenarios of predicted values of wind, light, electricity and heat. Secondly, triangular or trapezoid fuzzy parameters are used to represent the uncertainty of wind, light, electricity and heat prediction errors, and the certainty constraints of CHP-MG are transformed into fuzzy chance constraints based on credibility theory. Thirdly, according to the clear equivalence class of fuzzy chance constraints, the chance constraints with triangular or trapezoidal fuzzy parameters are clarified, and the corresponding deterministic mixed integer programming model is formed. Finally, the rationality of the proposed model and method is verified by Matlab/Cplex simulation, which provides a reliable economic scheduling scheme for CHP-MG. 

combined heat and power microgrid (CHP-MG), economic dispatching, uncertainty of source and load; fuzzy chance constraints, scenario generation

提升热电联供型微网(CHP-MG)在恶劣环境下的可靠运行能力, 在风光电热典型场景的基础上, 提出考虑源荷双重不确定性的CHP-MG模糊经济调度策略。首先, 采用拉丁超立方抽样(LHS)与K-means聚类相结合的方法生成风光电热预测值的典型场景。然后, 应用三角形和梯形两种模糊参数, 表示风光电热预测误差的不确定性, 并基于可信性理论将CHP-MG的确定性约束转变为模糊机会约束。接着, 根据模糊机会约束的清晰等价类, 将含三角形和梯形模糊参数的机会约束清晰化, 形成对应的确定性混合整数规划模型。最后, 通过Matlab/Cplex仿真实验, 验证所提模型及方法的合理性, 为CHP-MG提供可靠的经济调度方案。